Juliana Wang

Hybrid Strategy for Enhancing Longevity of Quantum Computing Systems

Started Oct. 3, 2024

Abstract or project description

The student is exploring various quantum computing methods with a particular focus on the critical role of coherence times in the performance and reliability of quantum systems. Her project will investigate the factors that influence coherence times across one or different quantum computing architectures, such as superconducting qubits and trapped ions. Through a combination of literature review and simulations, she is analyzing current approaches to extending coherence times and assessing their practical implications. The ultimate goal of her research is to identify strategies for optimizing quantum hardware to support more stable and scalable quantum operations.

Using Machine Learning For Exoplanet Classification

Started Aug. 10, 2023

Abstract or project description

Abstract With aims of discovering potential candidates and using that new found information to analyze the composition of the world as we know now, many efforts have been placed in to conduct research efficiently and accurately. With multiple methods for exoplanet detection such as shadow searching, the data produced from these methods still require interpretation to reach a conclusion (e.g. is there a dip in the light curve? ), which is why machine learning has recently come into the scene of astronomy with its potential to be trained for image classification tasks, requiring only a couple of seconds to a couple of minutes to complete their task. This paper used Convolutional Neural Networks (CNN), a type of Machine Learning specifically designed to classify images, and achieved a curve with an area-under-curve coverage of 0.91.